A National Framework for Infusing Information Technology in the Decision Support Process Dr. John Trimble1 and Andrew Nyamvumba2 1 Systems and Computer Science Department Howard University, Washington DC, usa,
[email protected] 2 Tshwane University of Technology, South Africa Key Words: Knowledge management, decision support systems, e-governance, web portals, ICT educational strategy
ABSTRACT
This study is based on an examination of the decision support needs of underdeveloped and developing countries and draws largely on our current work in Rwanda. This effort centers on a comprehensive framework for an information technology based decision support system (ITDSS). It addresses decision support at the national and local levels. The strategies and benefits of informed decision making at the central level are contrasted with the strategies and benefits of involving the broader population in decentralized decision making. Particular detail is provided on the strategy to infuse the necessary training and education in the national education process. The focus of this education strategy is on the tertiary level, but extends to recommendations to K-12 and community based education. The intent of this work is to draw on previous studies, as well as an examination of current conditions to detail a framework for IT-based decision support that national policymakers can consider as a guideline for developing, enhancing and assessing their knowledge-based decision support process. INTRODUCTION
Every day the world becomes more globally connected. As a result our daily economic and social lives are becoming more and more knowledge-driven. The challenge is for individuals, organizations and nations to plan for more effective knowledge management to aid in decision making at all levels. Computing researchers and academics will play a role in the organization and development of decision support software and techniques to facilitate all levels of decision-making. E-governance and e-government have unique roles in this knowledge management decision support system partnership. They have the ability to contribute significantly to more effective governmental administration on all levels and more effective efforts by governments to empower the people. Academics have a particular task to further curriculum development at all levels to better prepare future participants in this scenario of: knowledge management – computer based decision support systems – more effective e-governance. The collaborative, distributed nature of this scenario makes using content management systems to develop web portal based Knowledge and decision support systems a meaningful alternative. METHODOLOGY
This effort starts by clarifying what is knowledge, knowledge management and a decision support system (DSS), based on current work. This follows with a close 258
examination of DSS’s role in e-governance. Based on the work and future plans of Information Decision support Centers (IDSCs) in Egypt and Rwanda we propose 1) a framework for DSS development to enhance e-governance and 2) an educational strategy to complement that framework. KNOWLEDGE
In projecting the role of knowledge management, a concise definition of knowledge must be forwarded. This definition must distinguish knowledge from information and data. These three terms are often used interchangeably and in many instances inconsistently and contradictorily. “Knowledge is understanding gained through experience or study. It is “know-how” or a familiarity with the way to do something that enables a person to perform a task. It may also be an accumulation of facts, procedural rules, or heuristics.”[1] This broader definition of knowledge includes ‘facts’ which in many instances are classified as information. “Knowledge is a more subjective way of knowing and is typically based on experiential or individual values, perceptions, and experience.”[2] This narrow definition of knowledge excludes much of what is classified as explicit knowledge. A middle ground is more appropriate. Knowledge is ‘information about information’. Knowledge can be concisely defined as rules, guidelines, decisions, algorithms or processes that act on information. Knowledge is distinguished from information in that knowledge implies real or potential action. In contrast data is a string of signals with no assigned meaning. Information is data with an assigned meaning. Information can be simple facts such as my weight = 180 pounds or more complex information structures such as a database of student information that includes names, addresses, id numbers, courses, grades, etc.. Part of the confusion on distinguishing information and knowledge is the fact that most information implies knowledge. For example the ‘class average = 74.5’ implies the knowledge on how to calculate the mean from a set of individual grades. The equations and the action of the calculations represent the knowledge and the practice of the knowledge. However the individual grades and the class average are simply information. KNOWLEDGE STRUCTURES
Knowledge can be captured in a wide range of knowledge structures. Knowledge structures can be placed in four broad categories: graphical representations, logic, prose, and mixed approaches. Examples of graphical representations are decision trees, causal diagrams, semantic networks and ‘stock and flow diagrams’. Logic knowledge structures are grounded in proposition logic and predicate calculus. The most widely used logic knowledge structures are ‘rule based systems’ popularized by expert system development. Prose is by far the most widely used category of knowledge structures used in knowledge management systems. Prose structures can take many forms such as: scripts, recipes, scenarios, cases, guidelines and reports. These prose structures follow particular formatting rules that facilitate their utilization.
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KNOWLEDGE MANAGEMENT (KM)
The definitions of knowledge management range from the simple and straightforward “doing what is needed to get the most out of knowledge resources”[3] to Dalkir’s set of contextual definitions captured in table 1 below. Business Perspective
Cognitive Science Perspective
Process/technology perspective KM is a business activity with Managing Knowledge (the KM is the concept under 2 primary aspects: treating the insights, understandings and which information is knowledge component of practical know-how), the turned into actionable business activities as an fundamental resource that allows knowledge and made explicit concern of business us to function intelligently. available effortlessly in a and making a direct Knowledge is one, if not THE, usable form to the people connection between an principal factor that makes who can apply it. A virtual organization’s intellectual personal, organizational, and repository for relevant assets and positive business societal intelligent behavior information critical to results. possible tasks performed daily. Table 1 Contextual Definitions of Knowledge Management (adapted from Dalkir)
As the world becomes more globally connected our daily economic and social lives are becoming more and more knowledge-driven. Individuals, organizations and nations must be more conscious of this and plan for effective knowledge management. The task of knowledge engineering practitioners and researchers is to advance the science and art of knowledge management to keep pace with advances in information and communication technology (ICT). The definition and intent of knowledge management may vary given the context. However, all knowledge management systems must be concerned with best practices, rare expertise and complex knowledge practice. LINKING KNOWLEDGE TO DECISION SUPPORT
Generally a knowledge management system is based on a particular ‘domain of knowledge’. This domain can reflect a scientific discipline such as Botany or an organizational structure such as Umutara Polytechnic University. Knowledge outside of the principal domain can be used to manipulate the domain knowledge to assist in the decision making process. This assisting knowledge is classified as ‘decision support techniques’ and decision support software’. The relationship is evident in figure 1 below.
Figure 1 “Linking Knowledge to Decision Support”
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DECISION SUPPORT SYSTEMS
A Decision support system combines intellectual resources (information and knowledge) of individuals and organizations with computing and communication technology to improve the quality and timeliness of decisions. It uses a computer-based system to support decision-making. Early decision support computing environments were isolated dedicated systems. The most recent wikipedia definition of DSS “A properly-designed DSS is an interactive software-based system intended to help decision makers compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems and make decisions” [4] shows the shift to interactive collaborative decision making. The decision support process should cover 1) approaches to decision-making, 2) techniques for decision-making and 3) technologies for decision-making. In addressing approaches to decision making the concerns are philosophical and ideological perspectives, critical, scientific and system thinking, and the role of collective decision-making versus individual decision-making. There is a wide range of decision-making techniques that can be considered such as: group meeting where consensus is required, individual and group ranking techniques and the nominal group technique. Decision support technologies automate communication and management techniques where relations of production are key. Decision making technologies are built using a variety of software approaches such as 1) intelligent systems (software agents, particularly search agents; expert systems; case-based reasoning); 2) Operation research / Decision Science (math programming, inventory theory and supply chain mgmt, discrete simulation (grounded in queueing theory and Markov decision processes)); and 3) system dynamics (based on continuous simulation, grounded in closed feedback loop). DECISION SUPPORT AND E-GOVERNANCE
“e-Governance is a growing phenomenon within public sector institutions around the world and is emerging as a significant discipline within the field of public administration and management in general. … The concept of e-Governance is evolving and efforts to stabilize and clarify its operational implications must be made.”[5] The combination of knowledge repositories and decision support tools and techniques combined under a e-governance agenda can provide a powerful environment for empowering the public in the governance process. However “the debate regarding e-Governance is most often polarized between those who feel that ICTs will enhance the participation of citizens in the government policy decision-making process, and those who feel that it will simply be business as usual via a new medium.”[5] Government, ICT practitioners, and academics all have a role in assuring that it is not ‘business as usual’ by working to assure that the design and implementation of egovernance is ‘appropriate technology’. “The National Center for Digital Government seeks to apply and extend the social sciences in research at the intersection of governance, institutions and information technologies.”[6] This effort should promote a people centered e-governance development.
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The public awareness, in general, of the potentials of the advances in ICT has led to increased expectations of government efficiency and access. This will serve to increase pressure on policy makers to make e-governance more people-centered. “Recent advances in information and communication technologies (ICTs) have redefined citizens’ expectations of the government and its services”.[7] Punia focuses on communication and coordination between departments in the workflow and concludes “To facilitate coordination between independent and autonomous government departments, public private process structure with an independent third party monitoring may provide a feasible solution.”[7] Misuraca examines the implementation of e-governance strategies in Ghana, Senegal, South Africa and Uganda; and concludes “there is no single way of introducing ICTs ” in the governance process. Their study recognizes that “local languages and illiteracy constitute a barrier to access of information as well as lack of available skills to operate and maintain the physical infrastructure, as well as develop and maintain software”.[5] Our personal experience in Rwanda confirms this reality. Most of Africa lacks the ICT personnel to develop and maintain an ICT-based governance process. One solution is orienting the educational process to address this shortage and developing a national ‘information, knowledge and decision support center’ to implement a long-range national and continental strategy of e-governance. INFORMATION DECISION SUPPORT CENTERS
As part of their ICT plan 2005-2010, Rwanda intends to establish a National Information, Knowledge and Decision support center.[8] They indicate the purpose of the center will be to provide “valid and robust information for use in decision-making by key central authorities.” I will focus on the analysis of data and information required by such agencies as the Presidency, the Cabinet, the Parliament, various Ministries and Agencies. Rwanda identified Egypt’s IDSC as a model. Egypt’s IDSC Center identified five national projects categories that are to reflect their objectives listed in table 2 below: 1) decision support in strategic issues; 2) technological infrastructure; 3) information provision; 4) human resources development and 5) development of the administrative environment.[9] Egypt’s ‘Information and Decision Support Center (IDSC) Objectives To Strategically identify opportunities and challenges confronting the Egyptian Government in implementing its programs. To Support implementation of public policies and decisions through carrying out state-of-the-art policy research leading to solutions to the reform and development challenges facing Egypt. To disseminate our findings and views through a regular flow of publications and public events. To develop regional and international networks/ partnerships, to exchange know-how and research, which will result in the integration of international best practices in government
Table 2 IDSC Objectives ROLE OF WEB PORTAL DEVELOPMENT
Web portals provide a Content Management Framework System that also 1) Builds connections with outside resources; 2) Brings many tools to one convenient Location and 3) Supports Dynamic Customization and Personalization. The private sector has seen extensive use of web portal development. In recent years non-profit and government organizations have begun to build sites using portal development tools. Kastel identifies four
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layers of an Enterprise Portal, from top to bottom: business layer, functional layer, administration layer and portal platform layer. Key components of the functional layer are single sign-on, workflow and collaboration. Much of our concern in constructing an egovernance portal lies with the administrative layer that handles: user management, content management and document management.[10] The importance of content management is apparent in that many of the portal development tools are classified as ‘content management systems’. While major computing companies, such as IBM Microsoft, Oracle and SAP are portal vendors, the open source community has developed several high quality content management systems that can be used to develop and maintain a substantial web portal. Bonfeld compares the three leading open source contenders: Joomla, Drupal and Plone. The article concludes “For simpler requirements or lower budgets, Joomla, or possibly Drupal, should suit your needs. If you need something powerful and proven, and are willing to commit the resources to make it happen, Plone is likely to meet your need, but Drupal is also worth a look”.[11] Look for the open source portal tool set to continue to develop. New tool features and additional support (online videos, user groups, books and conferences) will make it even easier to quickly develop and maintain decision support portals. FRAMEWORK FOR IT BASED NATIONAL DSS
“While organizational leaders and managers must manage as knowledge leaders, they must be aware of the relationship between knowledge and those who possess it. Obtaining individual cooperation and motivation to be part of teams and groups is essential in making knowledge sharing the core of effective knowledge management.”[12] Not only do all government workers possess and use knowledge, but all citizens possess and use knowledge. A comprehensive framework for decision support development must address knowledge development and sharing from the highest leadership to the common citizen. The table below serves as a starting framework for this process. PARTICIPANTS National leadership: President, Prime Minister, Cabinet, etc.
Local leadership and technical workers: Secretary generals, sector, district and provisional leaders Citizens
TOOLS / STRATEGIES -Operation Research Models, -Simulation, -System Dynamics, -Statistical analysis -Collaboration tools, -Operation Research models, -E-learning tools, -Document sharing on portal
-Regular update of content -Diverse ‘how to do’ content -Elicit citizen inputs (i.e. surveys, petitions) Table 3: Framework for Decision Support Processes
BENEFITS -Better central planning -Better national assessment -Better international linkage
-Decentralized work plans -Larger segment of trained e-ready government workers -More collaboration across organizations and regions -Increase democracy -More satisfied population -Channel more creativity -EMPOWER THE PEOPLE
The implementation of this framework requires governmental support at all levels. However, it requires a strong commitment on the part of central or national government leaders to involve the general citizenry and commit to the necessary training to make egovernance a reality.
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ADDRESSING EDUCATIONAL NEEDS
The implementation of any effective e-governance strategy requires the trained personnel. In the case of most of Africa, the extreme shortage of personnel capable of implementing and maintaining information and knowledge-based systems requires a comprehensive, aggressive educational strategy. The educational strategy is divided into two parts. The first addresses the general needs – preparation at secondary school level, general education at university level for all students, and community based education. Table 4 below addresses these needs. The 2nd part deals with training ICT students at the university level to play a leading role in the future of knowledge-based decision support systems. This curriculum is contained in Table 5. It assumes a student has completed the secondary curriculum and general university curriculum listed in Table 4. SECONDARY -Critical thinking -Computer skills -Student centered learning -Scientific inquiry -Introduction to systems
UNIVERSITY -Computer Skills -Development Studies -Web utilization -Appropriate Technology -Critical Thinking
COMMUNITY -Computer Skills -Web utilization -Introduction to Systems -Appropriate Technology -Critical Thinking -Development Studies Table 4: General Educational needs for Knowledge society ICT CORE COURSES ADVANCED COURSES -Problem solving and programming -Operation Research -Web development -Statistical analysis and data mining -Introduction to modeling and simulation -System Dynamics -Database design -Knowledge management -Data structures and algorithms -AI and expert systems -Data communications and networks -Web services -Probability and Statistics -Portal development Table 5: Curriculum for university degree in Knowledge systems.
CONCLUSIONS A national strategy to achieve more effective use of computer-based decision support processes should start with clarification on what knowledge is. A knowledge management system that focuses on decision support is not only a knowledge repository of a given domain knowledge, but must include techniques and technologies that assist in decision-making. The inclusion of this decision-making component in an e-governance strategy requires 1) a comprehensive evolving national decision support system strategy and 2) and aggressive educational strategy. The educational strategy must be all inclusive – addressing students at secondary and tertiary level as well as community members that are not students. The decision support strategy must address training and tools for the highest administration (national leadership) to the general citizen.
A comprehensive strategy of this type will serve to set and monitor a strong national development agenda, as well as channeling the creativity of the broad citizenry. Most importantly it will empower the people, thereby contributing to appropriate technology.
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ACKNOWLEDGEMENTS
We must acknowledge are colleagues at RITA and Umutara Polytechnic University for their assistance. We must also acknowledge Howard University for giving the primary author a leave of absence between 2006-2008 making much of this work possible REFERENCES
[1] Awad, E (1996) Building Expert Systems Principles, Procedures, and Applications, West Publishing Company, St. Paul, MN [2] Dalkir, K (2005) Knowledge Management in Theory and Practice, Elsevier, Oxford [3] Becerra-Fernandez, A. Gonzalez, R. Sabherwal (2004) Knowledge Management Challenges, Solutions, and Technologies, Pearson/Prentice Hall, Upper Saddle River, NJ [4] definition of decision support systems, (last visit in September 2008) http://en.wikipedia.org/wiki/Decision_support_system [5] Misuraca, G (2006) “e-Governance in Africa, from theory to action: a practical-oriented research and case studies on ICTs for Local Governance” Proceedings of 2006 International Conference on Digital government research, San Diego CA [6] Fountain, J and D. Lazer (2005) “The National Center for Digital Government Integrating Information and Institutions” Proceeding of National Conference on Digital Government research, Atlanta GA [7] Punia, D and K. Saxena (2004) “Managing Inter-organisational Workflows in eGovernment Services” Proceedings 6th International Conference on Electronic Commerce [8] Government of Rwanda (2006) “An Integrated ICT-led Socio-Economic Development Plan for Rwanda 2006-2010”, http://www.rita.gov.rw/IMG/pdf/NICIfinal.pdf [9] Egypt’s Information Portal (last visit September 2008) http://www.idsc.gov.eg/ [10] Kastel, B (2003) Enterprise Portals For the Business & IT Professional. Competitive Edge International. Sarasota, FL [11] Bonfeld, B and L. Quinn (2008) “Comparing Open Source CWSes: Joomla, Drupal, and Plone” http://www.idealware.org/articles/joomla_drupal_plone.php [12] Mcfarlane, D. (2008). Effectively Managing The 21st Century Knowledge Worker. Journal of Knowledge Management Practice, Vol. 9, No. 1, March 2008
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